卫星互联网业务智能识别分类算法与仿真

doi:10.11959/j.issn.2096-8930.2022023

Abstract

Abstract:

With the continuous growth of task requirements and the increasing types of access services, new challenges are raised to the multi-service collaborative transmission capability and the global scheduling capability of network resources of satellite Internet.It is necessary to diff erentiate the services carried by it to optimize resource allocation to meet the service quality assurance requirements of satellite internet multi-service.A business intelligence identifi cation and classifi cation algorithm for satellite dynamic network was proposed.By analyzed the connectivity between satellites, a spatio-temporal steady state diagram was established, the dynamic satellite network topology was determined, and a satellite simulation network was constructed.Sampling to form a training data set, a business intelligence recognition method based on grayscale image was proposed, and the captured data packet was converted into a grayscale image as the input of the algorithm for training and identifi cation under the satellite dynamic scene.The results showed that with the increase of the number of iterations, the recognition accuracy increases, and the recognition accuracy was 97% or more, which verifi ed the eff ectiveness of the proposed algorithm and provided technical support for the development of satellite internet space payloads.

Key words: satellite internet, dynamic network, business intelligence identifi cation, service quality

CLC Number:

TN927+.2

Tao CUI, Zhiyuan REN, Jun LI, Qinggui TAN, Jingling LI, Wei LIANG. Intelligent Identifi cation and Classifi cation Algorithm and Simulation of Satellite Internet Business[J]. Space-Integrated-Ground Information Networks, 2022, 3(2): 72-80.

Figures/Tables 13

References 26

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